The Oomplet dataset toolkit as a flexible and extensible system for large-scale, multi-category image generation by John P. Kasarda, Angela Zhang, Hua Tong, Yuan Tan, Ruizi Wang, Timothy Verstynen, Michael J. Tarr

“…Abstract The modern study of perceptual learning across humans, non-human animals, and artificial agents requires large-scale datasets with flexible, customizable, and controllable features for distinguishing between categories. …”
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Comprehensive Analysis of ZVS Operation Range and Deadband Conditions of a Dual H-Bridge Bidirectional DC-DC Converter with Phase Shift Control by Ahmed Hamed Ahmed Adam, Jiawei Chen, Salah Kamel, Hamed Zeinoddini‐Meymand

“…This study offers a thorough examination of the zero voltage switching (ZVS) operation range and deadband conditions for a bidirectional DC-DC converter with phase shift control, featuring dual H-bridge. The analysis considers the soft switching range of the DAB converter, accounting for the impact of the headband and the ZVS capacitor. …”
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Localized Development and Application of Controller for Wind Turbines by YE Wei, YU Yong, LI Jun, YAN Zhi

“…The control system for MW level WTGs based on the domestic controller featuring autonomous controllability was proven to be autonomously controllable, safe and reliable.…”
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insilico.mutagenesis: a primer selection tool designed for sequence scanning applications used in directed evolution experiments by Ulrich Krauss, Thorsten Eggert

“…In anticipation of downstream cloning steps, the primer design tool also includes a restriction site control feature alerting the user if unwanted restriction sites have been introduced within the mutagenesis primer. …”
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Kajian Aerodinamika Pada Model Kendaraan dengan Penerapan Kontrol Aktif Suction by Rustan Tarakka, Nasaruddin Salam, Jalaluddin Jalaluddin, Wawan Rauf, Muhammad Ihsan

“…The rear part of the vehicle model is equipped with an active control feature in the form of a suction with a slant angle (α) of 35^°. …”
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Multi‐task learning using GNet features and SVM classifier for signature identification by Anamika Jain, Satish Kumar Singh, Krishna Pratap Singh

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Pancreatic β-cell regeneration in situ by the ALK3 agonist THR-123 by Silvia Álvarez-Cubela, Isabella D. Altilio, Mayur Doke, Dagmar Klein, Alejandro Tamayo, Óscar Alcázar, Carlos García Santana, Mirza Muhammad Fahd Qadir, Charles García Alver, Francis Cruz, Olivia Biggs, Jorge David Tovar Castro, Belén Navarro-Rubio, Camillo Ricordi, Alejandro Caicedo, Peter Buchwald, Ashutosh Agarwal, Elisa Oltra, Ricardo Luis Pastori, Juan Domínguez-Bendala

“…These islets, unlike those from non-diabetic controls, feature an extensive intrainsular network of ductal tissue. …”
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TRE-DSP: A traceable and revocable CP-ABE based data sharing scheme for IoV with partially hidden policy by Yousheng Zhou, Rundong Peng, Yuanni Liu, Pandi Vijayakumar, Brij Gupta

“…Due to its flexible and efficient fine-grained access control feature, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is suitable for data sharing in IoV. …”
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A deep biometric hash learning framework for three advanced hand‐based biometrics by Huikai Shao, Dexing Zhong, Xuefeng Du

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Research on Iterative Learning Method for Lower Limb Exoskeleton Rehabilitation Robot Based on RBF Neural Network by Jing Li, Huimin Jiang, Moyao Gao, Shuang Li, Zhanli Wang, Zaixiang Pang, Yang Zhang, Yang Jiao

“…We propose a novel control strategy integrating iterative learning with RBF neural network-based sliding mode control, featuring a single hidden-layer pre-feedback architecture. …”
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Assist-as-Needed Control of a Shoulder Rehabilitation Robot Using a Virtual Biomechanical Model and Online Stiffness Adaptation by Muhammad Faizan Shah, Prashant K. Jamwal, Mergen H. Ghayesh, Shahid Hussain

“…Assistance coefficient <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>(t), is then dynamically updated based on the user&#x2019;s measured interaction force, increasing support when effort is low and reducing it when active participation improves. The AAN controller features a gradient-based online stiffness learning mechanism, enabling the system to dynamically adjust joint stiffness during movement based on tracking errors and interaction forces. …”
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Design of Matching and Decoupling Networks With Radiation Pattern Control for Two-Element Antenna Arrays by Son Vu, Hung Luyen

“…We present an analytical approach for designing a matching and decoupling network (MDN) with radiation pattern control feature for two-element arrays. The antenna radiation pattern can be synthesized by formulating the S-matrix of the MDN to provide the desired excitation signals to the two antenna elements. …”
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Investigation of parallel joint density thresholds for granite tunnel failure based on physical model experiments and multiscale monitoring techniques by Huai-Sheng Xu, Shao-Jun Li, Ding-Ping Xu, Quan Jang, Liu Liu, Min-Zong Zheng, Xu-Feng Liu

“…Their failure mode was primarily joint-controlled, featuring macro-block structural failure as the dominant pattern and extensive stress-weakened zones due to parallel joint network effects. …”
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Evaluating soil erosion zones in the Kangsabati River basin using a stacking framework and SHAP model: a comparative study of machine learning approaches by Javed Mallick, Saeed Alqadhi, Swapan Talukdar, Md Nawaj Sarif, Tania Nasrin, Hazem Ghassan Abdo

“…Random Forest (RF), (Deep Neural Networks) DNN, Convolution Neural Network (CNN), and stacking (Meta model) models were used to map soil erosion susceptibility based on the inventory map and controlling features. The RUSLE model revealed five erosion zones with soil loss rates ranging from very low (less than 9 t/ha/year) to very high (above 43 t/ha/year). …”
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Exploratory development of human–machine interaction strategies for post-stroke upper-limb rehabilitation by Kang Xia, Xue-Dong Chang, Chong-Shuai Liu, Yu-Hang Yan, Han Sun, Yi-Min Wang, Xin-Wei Wang

“…For robot-in-charge and therapist-in-charge strategy, the desired and measured angle-time curve present good correlation, with low phase difference, which serve the purpose of real-time control. Featuring the patient-in-charge strategy, Kernel Density Estimation (KDE) result suggesting reasonable sensor-machine-human synergy. …”
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